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A Perspective on Artificial Intelligence in ManufacturingIntroduction

A Perspective on Artificial Intelligence in Manufacturing: Introduction [This chapter introduces Artificial Intelligence (AI) as well as manufacturing and draws the links between them. AI technology has been used in manufacturing for decades, on complex decision making, in support of the manufacturers, in their business processes. AI has been studied since the 1940s, however, it is only recently that scientists and industry practitioners are getting closer to effectively exploiting its potential since AI technologies have become more mature and affordable. In principle, AI can be understood as “software (and possibly also hardware) systems, designed by humans that, given a complex goal, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data reasoning on the knowledge, or processing the information, having derived from this data and deciding on the best action(s) to be taken to achieve the given goal”. The historical evolution of AI is presented in four upsurge periods, driven by improvements in relevant technologies. At the same time, manufacturing can be defined as the transformation of materials and information into goods for the fulfilment of human needs and it is one of the primary wealth creation activities for any nation besides contributing significantly to employment. Decision -making in manufacturing considers four classes of attributes, namely cost, time, quality, and flexibility. These attributes are discussed and examples of AI applications, related to optimization and decision making of these attributes, are provided. At the end a three-layered taxonomy into process, equipment and systems are presented. This taxonomy will be used for discussing applications of AI in the next chapters.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Perspective on Artificial Intelligence in ManufacturingIntroduction

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Publisher
Springer International Publishing
Copyright
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
ISBN
978-3-031-21827-9
Pages
1 –14
DOI
10.1007/978-3-031-21828-6_1
Publisher site
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Abstract

[This chapter introduces Artificial Intelligence (AI) as well as manufacturing and draws the links between them. AI technology has been used in manufacturing for decades, on complex decision making, in support of the manufacturers, in their business processes. AI has been studied since the 1940s, however, it is only recently that scientists and industry practitioners are getting closer to effectively exploiting its potential since AI technologies have become more mature and affordable. In principle, AI can be understood as “software (and possibly also hardware) systems, designed by humans that, given a complex goal, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data reasoning on the knowledge, or processing the information, having derived from this data and deciding on the best action(s) to be taken to achieve the given goal”. The historical evolution of AI is presented in four upsurge periods, driven by improvements in relevant technologies. At the same time, manufacturing can be defined as the transformation of materials and information into goods for the fulfilment of human needs and it is one of the primary wealth creation activities for any nation besides contributing significantly to employment. Decision -making in manufacturing considers four classes of attributes, namely cost, time, quality, and flexibility. These attributes are discussed and examples of AI applications, related to optimization and decision making of these attributes, are provided. At the end a three-layered taxonomy into process, equipment and systems are presented. This taxonomy will be used for discussing applications of AI in the next chapters.]

Published: Jan 1, 2023

Keywords: Decision-making; Decision-making criteria; Manufacturing

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